The present disclosure is directed to an automated inspection system for detection of coating imperfections. Particularly, the disclosure is directed to an automated inspection system for detection of coating imperfections based on the method of “shape from shadows” (also called computational illumination or multi-flash imaging).
Gas turbine engine components, such as blades, vanes, disks, gears, and the like, may suffer irregularities during manufacture, such as spallation, machining defects, or inadequate coating, or may suffer wear and damage during operation, for example, due to erosion, hot corrosion (sulfidation), cracks, dents, nicks, gouges, and other damage, such as from foreign object damage. Detecting this damage may be achieved by images or videos for aircraft engine blade inspection, power turbine blade inspection, internal inspection of mechanical devices, and the like. A variety of techniques for inspecting by use of images or videos may include capturing and displaying images or videos to human inspectors for manual defect detection and interpretation. Human inspectors may then decide whether any defect exists within those images or videos. When human inspectors look at many similar images of very similar blades of an engine stage or like components of a device, they may not detect defects, for example, because of fatigue or distraction experienced by the inspector. Missing a defect may lead to customer dissatisfaction, transportation of an expensive engine back to service centers, lost revenue, or even engine failure. Additionally, manual inspection of components may be time consuming and expensive. Emerging 3D depth sensors might provide an alternative approach; however, it may be particularly difficult, time consuming, or expensive to directly 3D scan a component to an accuracy sufficient to detect shallow spallation or small manufacturing defects.